World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
6757
World Ranking
8052
National Ranking
3456

Ilias Diakonikolas publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Ilias Diakonikolas sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 215 publications — 52nd percentile

52% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Ilias Diakonikolas D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Ilias Diakonikolas sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 2017 - Fellow of Alfred P. Sloan Foundation

Overview

Ilias Diakonikolas is affiliated with the University of Wisconsin-Madison in the United States. Their research primarily focuses on the field of Computer Science, with significant contributions to several subfields including Artificial Intelligence, Statistics and Probability, Computational Mechanics, Computer Vision and Pattern Recognition, and Control and Systems Engineering.

The main topics they address in their work include:

  • Machine Learning and Algorithms
  • Statistical Methods and Inference
  • Machine Learning and Data Classification
  • Sparse and Compressive Sensing Techniques
  • Advanced Statistical Methods and Models
  • Bayesian Modeling and Causal Inference
  • Face and Expression Recognition

Their recent papers cover a range of themes and are published in diverse venues. Selected publications are:

  • "Near-Optimal Disjoint-Path Facility Location Through Set Cover by Pairs," 2020, published in Operations Research
  • "Robustly Learning any Clusterable Mixture of Gaussians," 2020, presented on arXiv (Cornell University)
  • "Outlier Robust Mean Estimation with Subgaussian Rates via Stability," 2020, presented on arXiv (Cornell University)
  • "Algorithms and SQ Lower Bounds for PAC Learning One-Hidden-Layer ReLU Networks," 2020, presented on arXiv (Cornell University)
  • "Near-Optimal SQ Lower Bounds for Agnostically Learning Halfspaces and ReLUs under Gaussian Marginals," 2020, presented on arXiv (Cornell University)

Frequent co-authors in their body of work include:

  • Daniel M. Kane
  • Nikos Zarifis
  • Christos Tzamos
  • Thanasis Pittas
  • Ankit Pensia

Their contributions are also visible across several publication venues, among which the most frequent are:

  • arXiv (Cornell University)
  • Operations Research
  • Communications of the ACM
  • SIAM Journal on Computing
  • IEEE Transactions on Information Theory

In addition to articles, they have published a book titled Algorithmic High-Dimensional Robust Statistics in 2023, through Cambridge University Press.

Ilias Diakonikolas has received recognition such as becoming a Fellow of the Alfred P. Sloan Foundation in 2017.

Best Publications

  • Small Approximate Pareto Sets for Bi-objective Shortest Paths and Other Problems

    Ilias Diakonikolas;Mihalis Yannakakis

  • Proceedings of the 33rd International Conference on Machine Learning (ICML 2016)

    Jayadev Acharya;Ilias Diakonikolas;Schmidt , J. Li, L.

  • Sever: A Robust Meta-Algorithm for Stochastic Optimization

    Ilias Diakonikolas;Gautam Kamath;Daniel M. Kane;Jerry Li

  • Robust Estimators in High-Dimensions Without the Computational Intractability

    Ilias Diakonikolas;Gautam Kamath;Daniel Kane;Jerry Li

  • Robust Estimators in High Dimensions without the Computational Intractability

    Ilias Diakonikolas;Gautam Kamath;Daniel M. Kane;Jerry Li

  • Optimal algorithms for testing closeness of discrete distributions

    Siu-On Chan;Ilias Diakonikolas;Gregory Valiant;Paul Valiant

  • Statistical Query Lower Bounds for Robust Estimation of High-Dimensional Gaussians and Gaussian Mixtures

    Ilias Diakonikolas;Daniel M. Kane;Alistair Stewart

  • Being Robust (in High Dimensions) Can Be Practical

    Ilias Diakonikolas;Gautam Kamath;Daniel M. Kane;Jerry Li

  • A New Approach for Testing Properties of Discrete Distributions

    Ilias Diakonikolas;Daniel M. Kane

  • Recent Advances in Algorithmic High-Dimensional Robust Statistics.

    Ilias Diakonikolas;Daniel M. Kane

  • Testing for Concise Representations

    I. Diakonikolas;H.K. Lee;K. Matule;K. Onak

  • Robustly learning a gaussian: getting optimal error, efficiently

    Ilias Diakonikolas;Gautam Kamath;Daniel M. Kane;Jerry Li

  • Efficient density estimation via piecewise polynomial approximation

    Siu-On Chan;Ilias Diakonikolas;Rocco A. Servedio;Xiaorui Sun

  • List-decodable robust mean estimation and learning mixtures of spherical gaussians

    Ilias Diakonikolas;Daniel M. Kane;Alistair Stewart

  • Bounded Independence Fools Degree-2 Threshold Functions

    Ilias Diakonikolas;Daniel M. Kane;Jelani Nelson

  • Learning poisson binomial distributions

    Constantinos Daskalakis;Ilias Diakonikolas;Rocco A. Servedio

  • Bounded Independence Fools Halfspaces

    Ilias Diakonikolas;Parikshit Gopalan;Ragesh Jaiswal;Rocco A. Servedio

  • Small Approximate Pareto Sets for Biobjective Shortest Paths and Other Problems

    Ilias Diakonikolas;Mihalis Yannakakis

  • Testing identity of structured distributions

    Ilias Diakonikolas;Daniel M. Kane;Vladimir Nikishkin

  • High-dimensional robust mean estimation in nearly-linear time

    Yu Cheng;Ilias Diakonikolas;Rong Ge

  • Proceedings of the 29th Annual Conference on Learning Theory (COLT 2016)

    Ilias Diakonikolas;Daniel M. Kane;Alistair Stewart

  • Robustly Learning a Gaussian: Getting Optimal Error, Efficiently

    Alistair Stewart;Ilias Diakonikolas;Gautam Chetan Kamath;Daniel M Kane

Frequent Co-Authors

Daniel M. Kane
Daniel M. Kane University of California, San Diego
Rocco A. Servedio
Rocco A. Servedio Columbia University
Mihalis Yannakakis
Mihalis Yannakakis Columbia University
Gregory Valiant
Gregory Valiant Stanford University
Rong Ge
Rong Ge Duke University
Vitaly Feldman
Vitaly Feldman Apple (United States)
Xi Chen
Xi Chen Columbia University

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